{"title":"基于特征融合的英国城市地下地质异常检测方法","authors":"Xuemei Liu","doi":"10.15446/esrj.v26n3.103605","DOIUrl":null,"url":null,"abstract":"Engineering geological conditions include the nature of rock and soil, geological structure, landform, hydrogeological conditions, and adverse geological processes. Among them, faults, fissures, folds, karst, and lithology changes seriously affect the safety and construction cost of mountain tunnels, hydraulic tunnels, and other projects. For this reason, a new method based on feature fusion is proposed to detect the geological anomalies in London and Sheffield. It established a 3D raster data model oriented to attribute information modeling and visualization of urban underground space to obtain geological data. Based on this acquired data, authors adopted the feature-level fusion extraction method based on the multi-attribute geological abnormal body to extract, fuse, fill and surface the multi-attribute data of underground space geological data. Smooth processing can realize the detection of abnormal geological bodies in underground space. It has been proved that this method can be used in geological data display, feature extraction, feature fusion, and abnormal physical examination.","PeriodicalId":11456,"journal":{"name":"Earth Sciences Research Journal","volume":" ","pages":""},"PeriodicalIF":0.7000,"publicationDate":"2022-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A detection method of urban underground geological anomalies in the United Kingdom based on feature fusion\",\"authors\":\"Xuemei Liu\",\"doi\":\"10.15446/esrj.v26n3.103605\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Engineering geological conditions include the nature of rock and soil, geological structure, landform, hydrogeological conditions, and adverse geological processes. Among them, faults, fissures, folds, karst, and lithology changes seriously affect the safety and construction cost of mountain tunnels, hydraulic tunnels, and other projects. For this reason, a new method based on feature fusion is proposed to detect the geological anomalies in London and Sheffield. It established a 3D raster data model oriented to attribute information modeling and visualization of urban underground space to obtain geological data. Based on this acquired data, authors adopted the feature-level fusion extraction method based on the multi-attribute geological abnormal body to extract, fuse, fill and surface the multi-attribute data of underground space geological data. Smooth processing can realize the detection of abnormal geological bodies in underground space. It has been proved that this method can be used in geological data display, feature extraction, feature fusion, and abnormal physical examination.\",\"PeriodicalId\":11456,\"journal\":{\"name\":\"Earth Sciences Research Journal\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.7000,\"publicationDate\":\"2022-11-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Earth Sciences Research Journal\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.15446/esrj.v26n3.103605\",\"RegionNum\":4,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"GEOSCIENCES, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Earth Sciences Research Journal","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.15446/esrj.v26n3.103605","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"GEOSCIENCES, MULTIDISCIPLINARY","Score":null,"Total":0}
A detection method of urban underground geological anomalies in the United Kingdom based on feature fusion
Engineering geological conditions include the nature of rock and soil, geological structure, landform, hydrogeological conditions, and adverse geological processes. Among them, faults, fissures, folds, karst, and lithology changes seriously affect the safety and construction cost of mountain tunnels, hydraulic tunnels, and other projects. For this reason, a new method based on feature fusion is proposed to detect the geological anomalies in London and Sheffield. It established a 3D raster data model oriented to attribute information modeling and visualization of urban underground space to obtain geological data. Based on this acquired data, authors adopted the feature-level fusion extraction method based on the multi-attribute geological abnormal body to extract, fuse, fill and surface the multi-attribute data of underground space geological data. Smooth processing can realize the detection of abnormal geological bodies in underground space. It has been proved that this method can be used in geological data display, feature extraction, feature fusion, and abnormal physical examination.
期刊介绍:
ESRJ publishes the results from technical and scientific research on various disciplines of Earth Sciences and its interactions with several engineering applications.
Works will only be considered if not previously published anywhere else. Manuscripts must contain information derived from scientific research projects or technical developments. The ideas expressed by publishing in ESRJ are the sole responsibility of the authors.
We gladly consider manuscripts in the following subject areas:
-Geophysics: Seismology, Seismic Prospecting, Gravimetric, Magnetic and Electrical methods.
-Geology: Volcanology, Tectonics, Neotectonics, Geomorphology, Geochemistry, Geothermal Energy, ---Glaciology, Ore Geology, Environmental Geology, Geological Hazards.
-Geodesy: Geodynamics, GPS measurements applied to geological and geophysical problems.
-Basic Sciences and Computer Science applied to Geology and Geophysics.
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-Planetary Sciences.
-Engineering: Earthquake Engineering and Seismology Engineering, Geological Engineering, Geotechnics.